Computer Vision

The aims of this course are to introduce the principles, models and
applications of computer vision, as well as some mechanisms used in
biological visual systems that may inspire design of artificial ones.
The course will cover: image formation, structure, and coding;
edge and feature detection; neural operators for image analysis;
texture, colour, stereo, and motion; wavelet methods for visual coding
and analysis; interpretation of surfaces, solids, and shapes; data fusion;
probabilistic classifiers; visual inference and learning. Several of these
issues will be illustrated in the topic of face recognition.

Lectures

Goals of computer vision; why they are so difficult.
How images are formed, and the ill-posed problem of
making 3D inferences from them about objects and their
properties.